Navigating an Inevitable Transformation: A Reflection on Responsible Scientific Writing Large Language Models Integration and the RULE-AP Consensus

Large language models (LLMs) are reshaping scientific communication in Anesthesiology and Pain Medicine. The RULE-AP Delphi consensus – convening 53 editors-in-chief – proposes a regulatory framework that distinguishes legitimate assistance from intellectual abdication. We argue that LLMs offer genuine value for derivative tasks such as language polishing, reference formatting, and search strategy refinement, thereby reducing cognitive load and democratizing access for non-native English speakers. However, human authors must retain exclusive responsibility for hypothesis generation, result interpretation, and conclusions. LLMs cannot serve as authors; they lack legal standing, produce hallucinations, and cannot exercise clinical judgment. The proliferation of algorithmically generated manuscripts threatens to dilute the peer-reviewed literature and compromise AI training corpora – a self-reinforcing risk requiring urgent editorial vigilance. We further caution against using LLMs to generate peer-review reports, as doing so violates confidentiality and undermines the nuanced judgment that rigorous review demands. To preserve trust, we advocate for standardized AI Disclosure Statements in all submissions. Transparency is not a confession of weakness – it is the foundation of reproducible, accountable science. Education in responsible LLM use must become standard training for the next generation of researchers.